Machine Learning Operations Engineer

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Machine Learning Operations Engineer

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TEKsystems

TEKsystems has been supporting our client since early 2025 in the development and build of a product that enables customers to activate and reach highly qualified consumer audiences across the healthcare journey and various conditions from chronic illnesses to rare diseases. This product/solution went live earlier in the year and the team is now looking to add more capabilities, functions and continue to automate. The product details are available at https://www.iqviadigital.com/solutions/consumer-audiences.

Key Responsibilities

Design, build, and maintain MLOps pipelines for model deployment, monitoring, and lifecycle management.

Migrate machine learning workflows and models from Cloudera Machine Learning (CML) to Databricks.

Develop and optimize Databricks environments for data ingestion, model training, and real‑time serving.

Leverage Streamlit to create intuitive interfaces for ML models and workflows.

Automate data preprocessing, feature engineering, model experimentation, and deployment processes.

Implement and manage CI/CD pipelines tailored for machine learning workflows.

Monitor model performance and data drift, ensuring quality and reliability in production systems.

Collaborate with data scientists to transform prototypes into scalable production systems.

Manage Databricks clusters and infrastructure resources to ensure cost‑efficiency and availability.

Establish systems for automated logging, performance tracking, and alerting.

Document processes, workflows, and best practices to drive operational excellence.

Required Skills And Qualifications

Strong expertise in Python programming for machine learning and data processing.

Familiarity with the Streamlit framework for building user‑friendly ML applications.

Proven experience with Databricks Apps and environments for ML workflows.

Hands‑on experience migrating systems from Cloudera Machine Learning (CML) to alternative platforms.

Experience with Azure ML and storage related services.

Familiarity with CI/CD tools like GitLab CI.

Knowledge of data pipeline tools (e.g., Apache Airflow) and data governance practices.

Solid understanding of version control (Git) and ML model versioning tools (e.g., MLflow).

Strong problem‑solving skills and ability to thrive in a fast‑paced environment.

Preferred Skills

Familiarity with compliance frameworks for AI systems (e.g., GDPR, HIPAA).

Additional Skills & Qualifications

Natural Language Processing (NLP). Useful for potential future roadmap items involving language models.

Data Engineering Tools & Practices. Knowledge of ETL processes, data modeling, and pipeline optimization.

Cloud Security & Compliance Awareness. Important in healthcare/pharma contexts for data privacy and regulatory compliance.

Experience Level Expert level

Job Type & Location This is a Contract position based out of Ottawa, ON.

Pay And Benefits The pay range for this position is $85.00 - $95.00/hr.

Workplace Type This is a fully remote position.

Seniority level Mid‑Senior level

Employment type Contract

Job function Engineering and Information Technology

The company is an equal opportunity employer and will consider all applications without regard to race, sex, age, color, religion, national origin, veteran status, disability, sexual orientation, gender identity, genetic information or any characteristic protected by law.

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